The present invention relates to a multiple-input-multiple-output (MIMO) wireless communication system and wireless communication apparatuses that are used in the MIMO wireless communication system.
In this field of technology, intensive studies are being made on wireless interfaces to improve communication capacities, communication speed, communication quality, resource utilizing rates, and the like. Particularly, in MIMO systems that have been attracting public attention recently, two or more antennas are provided at both the transmission end and the reception end, so that a multiple-input-multiple-output system is formed with wireless transmission channels. With a larger number of antennas for transmission and reception, the usability of space is increased, and the transmission capacity can also be increased.
FIG. 1 is a conceptual view of a MIMO communication system. For ease of explanation, the left side in FIG. 1 is the transmission end, and the right side is the reception end, though each end normally has both transmitting and receiving functions. A transmission signal vector x(t)=(x1(t), x2(t), . . . , xM(t))T is transmitted through each of M antennas at the transmission end. Here, T represents “transpose”, and M is an integer of 2 or greater. It is possible to add an adjustable weight μj to each of the M antennas. Here, j is an integer between 1 and M. Likewise, N antennas are provided at the reception end. Based on the signal received at each antenna, a reception signal vector y(t)=(y1(t), y2(t), . . . , yN(t))T is obtained. Here, N is an integer of 2 or greater, and may be either the same as M or different from M. It is also possible to add an adjustable weight vi to each of the N antennas at the reception end. Here, i is an integer between 1 and N.
In this case, the relationship between the transmission vector x(t) and the reception vector y(t) is expressed by the following equation:
                              y          ⁡                      (            t            )                          =                                                            ρ                M                                      ⁢                          Hx              ⁡                              (                t                )                                              +                      n            ⁡                          (              t              )                                                          (        1        )            
where H is a channel matrix that represents the transmission characteristics of the wireless transmission channels among the antennas, and the matrix elements hij represent the transmission characteristics (in a baseband representation) of the wireless transmission channel between the jth antenna of the transmission end and the ith antenna of the reception end. Here, i is an integer between 1 and N, and j is an integer between 1 and M. Accordingly, the channel matrix H is a matrix having N rows and M columns (N by M). Further, ρ represents the transmission power, and n(t) represents the noise vector that is introduced in the wireless transmission channels and is assumed to be expressed by an additive Gaussian noise vector. The noise components at any time can be evaluated from random numbers in accordance with a Gaussian distribution.
If knowledge of the channel matrix H is acquired by the reception end, the communication channel capacity (or the Shannon capacity) expressed as a ratio of (maximum) signal transmission speed to frequency (bps/Hz) can be evaluated by the following expression (2) with the expected value of the amount I of conditional mutual information as to the transmission vector x(t) and the reception vector y(t).
                              E          ⁡                      [                          I              ⁡                              (                                  x                  ;                                      y                    |                    H                                                  )                                      ]                          ≤                  E          ⁡                      [                          log              ⁢                                                          ⁢                              det                ⁡                                  (                                                            I                      N                                        +                                                                  ρ                        M                                            ⁢                                              HH                        *                                                                              )                                                      ]                                              (        2        )            
where: H represents the ergodicity obtained by evaluating the ensemble mean value using the time mean value; E[·] indicates that the term is the expected value; IN represents the unit matrix having a dimension N; [*] indicates that the term is a transposed conjugate; and det(·) represents a determinant of the matrix.
Further, if the knowledge of the channel matrix H is shared between the reception end and the transmission end, the communication channel capacity C can be expressed by the following equation (3):
                    C        =                              ∑                          i              =              1                        α                    ⁢                                    log              2                        ⁡                          [                              1                +                                                      ρ                    M                                    ⁢                                      λ                    i                                                              ]                                                          (        3        )            
where α and λi represent the number of ranks of the matrix expressed by HH* and the ith eigenvalue, respectively. Here, i is an integer between 1 and α.
MIMO wireless communication systems and the communication channel capacities are disclosed in the following Non-Patent Documents 1 through 4.
(Non-Patent Document 1)
I. E. Telatar, “Capacity of Multi-Antenna Gaussian Channels”, Bell Labs. Technical Memorandum, 1995 (See also “Europ. Trans. Telecommun.”), Vol. 10, No. 6, pp. 585–595, November–December 1999)
(Non-Patent Document 2)
G. J. Foschini and M. Gans, “On the Limits of Wireless Communication in a Fading Environment When Using Multiple Antennas”, Wireless Personal Commun., Vol. 6, No. 3, pp. 311–335, March 1998
(Non-Patent Document 3)
G. J. Foschini, “Layered Space-Time Architecture for Wireless Communication in a Fading Environment When Using Multiple Antennas”, Bell Syst. Tech. J., Vol. 1, No. 2, pp. 41–59, 1996
(Non-Patent Document 4)
J. B. Andersen, “Array Gain and Capacity for Known Random Channels with Multiple Element Arrays at Both Ends”, IEEE J. Sel. Areas in Commun., Vol. 18, No. 11, pp. 2172–2178, November 2000
In accordance with equation (3), the entire communication channel capacity C can be determined by the sum of the channel capacities Ci of communication channels that correspond to the eigenvalues λi of the matrix HH*. In that case, as the communication channel capacities Ci are proportional to the eigenvalues λi, the channel capacity of a communication channel corresponding to a small eigenvalue is small, and such a communication channel has a poor throughput and a high bit error rate. Accordingly, with a very small eigenvalue, it is difficult to use the channel capacity of the communication channel corresponding to the eigenvalue in actual wireless communications, and only a part of the entire communication channel capacity C can be used.